Counting the Dead: COVID-19 and Mortality in Quebec and British Columbia During the First Wave.

The first wave of the COVID-19 pandemic has led to excess mortality across the globe, and Canada has been no exception. Nonetheless, the pandemic experience has been very different across provinces, and the objective of this paper is to investigate these differences focusing on two extreme cases. We contrast the mortality experience of British Columbia with that of Québec to understand how large differences in mortality during the first wave of the pandemic emerged across these two provinces. We find that most of the differences can be found in excess mortality in institutions (nursing homes) and that travel restrictions, differences in how deaths are recorded, differences in the seasonality of the flu, or differences in how the pandemic spread across different economic segments of the population are unlikely explain these large differences. We document that the reported death toll from COVID-19 is about 30% larger than excess mortality in Quebec due to lower mortality from other causes of death, in particular malignant tumors, heart disease, and respiratory problems. We do not find evidence of an income gradient (measured by postal code level income) in relative excess death for the first wave.

La première vague de la pandémie de la COVID-19 a entraîné une surmortalité dans plusieurs pays à travers le monde, incluant le Canada. Par contre, l'ampleur fut bien différente à travers les provinces canadiennes et l'objectif de cette analyse est d'étudier ces différences en se concentrant sur deux provinces spécifiques. Pour ce faire, nous comparons la mortalité de la Colombie-Britannique avec celle du Québec pour tenter de comprendre les grandes différences observées entre ces deux provinces durant la première vague de la pandémie. On constate qu'une grande partie de la surmortalité différentielle est observée chez les personnes vivant en institutions de santé (maisons de soins). De plus, on remarque aussi que les restrictions concernant les déplacements internationaux, les processus d'enregistrement des décès, l'évolution de la grippe saisonnière ou les différences dans la façon dont la pandémie s'est propagée à travers les groupes sociaux-économiques de la population sont peu susceptibles d'expliquer ces grandes différences. Notre analyse montre que le nombre de décès attribués à la COVID-19 est d'environ 30% plus élevé que la surmortalité observée au Québec durant la première vague. Cet écart est, en partie, attribuable à une mortalité plus faible de d'autres causes de décès, en particulier les tumeurs malignes, les maladies cardiaques et les problèmes respiratoires durant la même période. Finalement, nous n'avons pas été en mesure de calculer un gradient de revenu (mesuré par le revenu au niveau du code postal) pour les décès excédentaires survenus lors de la première vague.Mots clés: excès de mortalité, COVID-19, institutions de santé, cause de décès.

Accounting for the Rise of Health Spending and Longevity.

We estimate a stochastic life-cycle model of endogenous health spending, asset accumulation and retirement to investigate the causes behind the increase in health spending and longevity in the U.S. over the period 1965-2005. Accounting for changes over time in taxes, transfers, Social Security, income, health insurance, smoking and obesity, and technological progress, we estimate that technological progress is responsible for half of the increase in life expectancy over the period. Substantial growth in health spending over the period is largely the result of growth in economic resources and the generosity of health insurance, with a modest role for medical technological progress. The growth in spending does not come from changes in a single source, but sources jointly interacted to increase spending: complementarity effects explain up to 26.3% of the increase in health spending. Overall, for those born in 1940, the combined changes in resources and health insurance that occurred over the period are valued at 35.7% of lifetime consumption.

Disease incidence and mortality among older Americans and Europeans.

Recent research has shown a widening gap in life expectancy at age 50 between the United States and Europe as well as large differences in the prevalence of diseases at older ages. Little is known about the processes determining international differences in the prevalence of chronic diseases. Higher prevalence of disease could result from either higher incidence or longer disease-specific survival. This article uses comparable longitudinal data from 2004 and 2006 for populations aged 50 to 79 from the United States and from a selected group of European countries to examine age-specific differences in prevalence and incidence of heart disease, stroke, lung disease, diabetes, hypertension, and cancer as well as mortality associated with each disease. Not surprisingly, we find that Americans have higher disease prevalence. For heart disease, diabetes, and cancer, incidence is lower in Europe when we control for sociodemographic and health behavior differences in risk, and these differences explain much of the prevalence gap at older ages. On the other hand, incidence is higher in Europe for lung disease and not different between Europe and the United States for hypertension and stroke. Our findings do not suggest a survival advantage conditional on disease in Europe compared with the United States. Therefore, the origin of the higher disease prevalence at older ages in the United States is to be found in higher prevalence earlier in the life course and, for some conditions, higher incidence between ages 50 and 79.

Substantial health and economic returns from delayed aging may warrant a new focus for medical research.

Recent scientific advances suggest that slowing the aging process (senescence) is now a realistic goal. Yet most medical research remains focused on combating individual diseases. Using the Future Elderly Model--a microsimulation of the future health and spending of older Americans--we compared optimistic "disease specific" scenarios with a hypothetical "delayed aging" scenario in terms of the scenarios' impact on longevity, disability, and major entitlement program costs. Delayed aging could increase life expectancy by an additional 2.2 years, most of which would be spent in good health. The economic value of delayed aging is estimated to be $7.1 trillion over fifty years. In contrast, addressing heart disease and cancer separately would yield diminishing improvements in health and longevity by 2060--mainly due to competing risks. Delayed aging would greatly increase entitlement outlays, especially for Social Security. However, these changes could be offset by increasing the Medicare eligibility age and the normal retirement age for Social Security. Overall, greater investment in research to delay aging appears to be a highly efficient way to forestall disease, extend healthy life, and improve public health.

The value of medical and pharmaceutical interventions for reducing obesity.

This paper attempts to quantify the social, private, and public-finance values of reducing obesity through pharmaceutical and medical interventions. We find that the total social value of bariatric surgery is large for treated patients, with incremental social cost-effectiveness ratios typically under $10,000 per life-year saved. On the other hand, pharmaceutical interventions against obesity yield much less social value with incremental social cost-effectiveness ratios around $50,000. Our approach accounts for: competing risks to life expectancy; health care costs; and a variety of non-medical economic consequences (pensions, disability insurance, taxes, and earnings), which account for 20% of the total social cost of these treatments. On balance, bariatric surgery generates substantial private value for those treated, in the form of health and other economic consequences. The net public fiscal effects are modest, primarily because the size of the population eligible for treatment is small. The net social effect is large once improvements in life expectancy are taken into account.

The benefits of risk factor prevention in Americans aged 51 years and older.

OBJECTIVES: We assessed the potential health and economic benefits of reducing common risk factors in older Americans. METHODS: A dynamic simulation model tracked a national cohort of persons 51 and 52 years of age to project their health and medical spending in prevention scenarios for diabetes, hypertension, obesity, and smoking. RESULTS: The gain in life span from successful treatment of a person aged 51 or 52 years for obesity would be 0.85 years; for hypertension, 2.05 years; and for diabetes, 3.17 years. A 51- or 52-year-old person who quit smoking would gain 3.44 years. Despite living longer, those successfully treated for obesity, hypertension, or diabetes would have lower lifetime medical spending, exclusive of prevention costs. Smoking cessation would lead to increased lifetime spending. We used traditional valuations for a life-year to calculate that successful treatments would be worth, per capita, $198,018 (diabetes), $137,964 (hypertension), $118,946 (smoking), and $51,750 (obesity). CONCLUSIONS: Effective prevention could substantially improve the health of older Americans, and--despite increases in longevity--such benefits could be achieved with little or no additional lifetime medical spending.